| Function Approximation |   |   | Partial Observability |   |   | Learning Methods |   |   | Ensembles |   |   | 
| Stochastic Optimisation |   |   | General RL |   |   | General ML |   |   | Multiagent Learning |   |   | 
| Comparison/Integration |   |   | Bandits |   |   | Applications |   |   | Robot Soccer |   |   | 
| Humanoids |   |   | Parameter |   |   | MDP |   |   | Empirical |   |   | 
| Failure Warning |   |   | Representation |   |   | General AI |   |   | Neural Networks |   |   | 
| All |   |   | 
 Artificial Intelligence: An Empirical Science
 Herbert A. Simon, 1995
    Details   
 Benchmarks, Test Beds, Controlled Experimentation, and the Design of Agent Architectures
 Steve Hanks,  Martha E. Pollack, and  Paul R. Cohen, 1993
    Details   
 Machine Learning as an Experimental Science
 Pat Langley, 1988
    Details   
 The Future of Data Analysis
 John W. Tukey, 1962
    Details